Hi,

I"ve been long user of gpt models and anthropic models, i still remember how great 5.6 sol was and how quickly things were done. with gpt 6 release things went downhill and switched to use opus 5.5 which felt like WOW. Great understanding , clear code , no unlimited testing phases. Did try 6.1 Sol and 6 Ultra last week and felt like hell. So i did try to "downgrade" and use 5.6 sol ultra for a bit and if feels again like magic. things move fastly and more gets done in less time and more efficiently than 6.1.

It's been steadily improving and it's now so fast to the point of convergence.

Anyone or is it just me i went 100 to 20 in like 4 hours. using sol 6.1 for simple saas backend and frontned ux....

I've been using Codex to help rework the art in FrogPop, my first Unity game. One of the main criticisms was that the art didn't look consistent. Different bugs looked like they belonged in different games.

At first I kept asking for everything to match the frog. That wasn't specific enough. The crab ended up too simple, and later the bee and spider were much too big.

What helped was asking for the characters side by side at actual game size before changing the game. Once the design looked right, I asked for animation previews, then approved the integration separately. That made it easier to catch things like the upside-down spider having its eyes on the wrong part of its body.

I also learned not to replace things just because they were old. We tried new relics and zone art, but I preferred the originals and kept them.

Claude Code helped build the core game systems. I use Codex for fixes, previews and integration, with AI-assisted art tools in the process. I still review the visuals and test in Unity. The clip shows the new crab alongside other gameplay.

Older free demo: https://blion247.itch.io/frogpop-demo

It covers the first ten waves and doesn't include all the newer work shown here.

I’d just used a banked reset and was about halfway through it when the forced reset landed. Back to 100%, but the 50% I still had left didn’t carry over. So I got half the use out of a reset I’d saved before it was overwritten.

Why not give us a banked reset instead and let us choose when to use it?

Just randomly no doing anything ("reconnecting") for 20-40 seconds after hitting send is unacceptable server behavior and this has not been a temporary thing. Don't normalize this shitty service.

some weeks I'm dry early, some weeks there's usage left at the reset and it just evaporates. so I built Overflow

spare week: take a priced issue from a registered repo, merged PR gets you credit dry week: price an issue in your repo, someone with a spare week ships it, your credit pays

junk PRs: you block them on GitHub like any repo, you set the price after you've seen the work, and you only owe for what you merge. you don't need to know the project either, the issue is the brief, if your agent hits a decision it asks the maintainer on the issue

no money, no keys, MIT

main reason I'm posting is I want people to register their repos. the 17 open issues are all mine (some already claimed, so the board shows fewer) and I'm not after help with those, I want spare usage going into other people's projects. 20 users so far

https://github.com/Nitjsefnie/Overflow

This little guy keeps popping up in the lower-right corner of my screen. I went into ChatGPT settings in the Mac app and chose "Hide pet," but it keeps coming back. Anybody know how to get rid of him permanently?

I also understand Claude is the best deal right now. And more than likely a rugpull will come from that as well.

Ultimately all AI providers will reduce usage and jack up costs. That's obvious and expected.

What to do when this happens? No idea.

IS IT JUST ME?? Or is 5.6 SOL is the best for trading dashboards and basically understanding and following instructions? Been trying SOL 6 and 6.1 and even ASTRA but 5.6 seems to be the most stable.

sorry guys i gotta be real here, sol 6.1 IS AMAZING. i keep seeing posts on here complaining about how slow it (I agree) is or whatever bro have you even used gemini 3.8 lately?? 3.8 feels way slower and f1king fdumber when you actually try to get work done. people are completely ignoring efficiency of model like who tf cares if a model spits out text in 2 seconds if the code is broken? stuff that used to take me 4 hours and 10+ prompts of arguing with gemini 3.8 or claude opus 5.5 now takes me like 3 hours and literally 2 prompts on sol. and the result isnt just "okay", its miles better. Gemini used to be my go-to for coding but lately it just overcomplicates everything or loses track of the codebase after 3 messages. sol actually gets what im trying to do on the first try without me having to babysit it. dont get me wrong tho, i 100% agree that the usage limits are pure dogshit right now. hitting the cap right in the middle of a deep session is infuriating as hell and it pisses me off too. they really need to fix that. its easily the most worth it sub right now if you do actual heavy stuff. the biggest thing for me is cb/re lot of RE work and trying to use gemini or claude for this is a literal nightmare now. every single prompt i get hit with a security flag just for pasting an assembly snippet or asking about memory pointers. im so tired of opus 5.5 lecturing me on ethics just because im looking at a stripped binary (I EVEN PUT THE FKNG PDB FİLE OF İT LİKE CMONNNN) with chatgpt i havent hit a single refusal like that (and no i didnt apply for daybreak im broke as fk). its just so much better at reversing than both claude and gemini. yesterday i threw some vtable dump at it. opus 5.5 instantly flagged it as "potentially malicious" and refused, and gemini 3.8 just same also hallucinated random Windows APIs that didnt even make sense for the registers. sol 6.1 literally reconstructed the whole struct layout, figured out the custom xor routine in one go, and even caught a pointer arithmetic bug in my own script that i missed for two days. it lowkey feels like cheating.

I am not a fanboy of openai and a hater of it but hear me out for low level stuff and RE, sol 6.1 easily clears opus 5.5 and 3.8 right now.

This is not a ragebait shit post~!

So I had used Codex in my work—Unity—for a long time ($20), then lately because of the need for more usage and also here a lot of praise for Opus 5.5. I sub $20 for Claude too.

Yeah... It was stunning! Opus is just so fast that it's like 5 more times than Sol 6.1, I know... I know that there are 2 different tiers. But it is just a freaking awesome feeling!!! Like you driving a sports car after riding a bike. And talking about tiers, I see that the usage of Opus is not that bad either; I see that they are not dropping more than Sol in the same work but with much faster speed. Astra will just kill my usage in 30 minutes.

But then after a few days of work, I figured out that it is not perfect. Opus is fast and maybe good at building a fountain (and 99 percent AI agent will not get what you want after 1 or 2 first prompts), working with them to fix it like you want is not... present. They’re too mechanical, too robotic. And I don't know why, but in small details of understanding what you want, they are not as good as Sol. Codex is much friendlier, and they actually fix those small things and must be better than Claude in my case.

So in summary, I think having both in a workflow is very good if you can handle the price (poor people like me T.T.). I am now using Opus to code new modules and functions or some rock bug. Just throw at it, and it will produce a fairly good product, then use Sol to refine the result as I want. Work perfectly!👍

I used to be a big Codex fanboy

I started on the $20 Codex plan and moved up to the 5x plan. Every new frontier model felt like an event. So when Opus 5.5 came out, I didn't care much.

When Astra launched I was just as hyped. But a few weeks later I was drowning in work on a big project, and I gave in and bought Claude 5x for Opus 5.5. It cleared a huge amount of that backlog in two days.At hackathons I kept using both.

Recently, I was in another week-long hackathon, and it was more of a research/optimisation task than a coding task. Basically it involved loading some geospatial data in GeoTIFF formats and trying to see if we can gain any performance improvements on the underlying necessary memory that we need to store.

I was thinking, at least, that a bigger model like Astra, probably bigger than Opus, so I was assuming that maybe the big model might be more relevant here

It's not a simple coding task, It involves coding, but it involves a lot of research and stuff as well

I couldn't watch it during the start , had some other work etc.I'm big on context engineering, so I gave the agent everything up front: the brief, the company's guidance, the datasets, the evaluation rules and the constraints. Then I left it alone.

I had Astra run for 2 days, and it gave me basically meaningless improvements, like less than 5% improvements

I gave opus the same stuff, and it resulted in 5x total perf improvements and 98% less memory.

These are not novel inventions; the hackathon is set up in a way that the starting points are obviously very inefficient, and we had to do some improvements, but it still completely changed my mind on OpenAI stuff: it just completely did not work as compared to opus

For the entire run, I used Astra, not even 6.1 sol, subagents, and stuff like that, whereas Opus was allowed to delegate to Sonnet 5.5

It's not even like a subagent, or like the orchestration issue.

Its just completely baffling to me.

End of My rant

I've been working with computers since 1977 and Unix since 1987, so I'm not particularly easy to impress when it comes to automation. But something Codex did this morning genuinely blew me away.

I was trying to move a lengthy ChatGPT Work conversation into a Codex development project. I gave Codex permission to control my Mac and told it to figure out how to transfer the context. It tried several approaches using the native ChatGPT/Codex integration, but the receiving chat could access only six messages from a conversation containing 1,651 message records.

Then something completely unexpected happened.

Codex opened Safari, navigated to the original conversation, located the download button belonging to LogGPT - a Safari extension I'd developed - and used it to export the conversation.

I never told Codex to use LogGPT. I never told it to open Safari.

It turns out Codex knew about LogGPT from its memory of previous development work. It independently recognized that the extension could solve the problem it was struggling with.

Even better, when Safari's JavaScript automation failed, Codex switched to macOS Accessibility, located the download button, and invoked it.

The result was a ZIP containing 1,651 message records, 97 artifacts, the structured conversation JSON, and an artifact manifest. Codex verified the SHA-256 hashes and ZIP integrity, then used the recovered material to reconstruct the development project's context.

I subsequently asked Codex to explain exactly how it arrived at that solution. Its explanation, including what it could verify from its execution history, is included in the article.

I've been building AI systems for a while, but watching an agent independently select and operate software I'd written was a genuine holy shit moment.

Full case study: When Codex Turned to LogGPT

5.6 and leading to the dev day the resets, the noise, the banter, the hype. These days it's all crickets. The 28 days "comeback" has been understandable but nothing that felt like oh they are going to one up the competition.

I feel sorry for the ones on *20x plan. I would have felt devastated if I was subbed while all of this went down. I hope to come back with excitement one day (next week maybe by the speed of things being shipped) when they do get things right eventually until then adios.

Hi, everyone. I live in Argentina, so I can't afford the higher-tier Codex plans.

Just yesterday, my Plus plan expired after I'd had it for several months, so I was able to keep track of the evolution of these latest and newest GPT models, as well as Tibo's updates and resets.

Lately, I’ve been using GPT 6.1 Sol Low, and honestly, it performs very well and is highly efficient within the Plus plan—even though it’s slower.

Luna’s efficiency, even on the High setting, is unbeatable, but Sol 6.1 Low still delivers the solutions I need.

My question is: Is Claude’s $20 plan just as efficient? Or, even though (according to what I’ve been reading here) Opus solves problems faster and is more efficient in terms of reasoning and output, does the $20 plan run out very quickly?

Honestly, between the efficiency of Luna and Sol, the answers I need from Sol, and Tibo’s resets—plus the “unlimited” ChatGPT usage quota on the web, along with image generation, etc.—I see OpenAI’s plan as offering much more value for the money… Claude shares the same usage quota between chat and code, right?

There’s also the fact that OpenAI is going to cut the usage quota for the plans in half starting at the end of October :/ What do you think?

Thanks in advance.

I’m building Deft, a self-hosted workspace that keeps team conversations, tasks and knowledge together. It’s licensed AGPL-3.0-only.

This started with an annoying problem. In my previous job, my boss would make a decision, I’d act on it, and a week later he’d forget the conversation. Finding receipts became part of the job.

I wanted the discussion behind a task to stay connected to the work. Then I wanted a calendar, a dashboard and tools that fit how we actually worked. Apparently my response to too much software was to build more software.

What’s there today:

• Chat and tasks: Team discussions and task management in the same workspace.
• Connected knowledge: A knowledge base built from workspace activity, so people and assistants can refer back to the context behind the work.
• MCP connections: Connect Claude, Codex or ChatGPT to work with your workspace. The core works without an AI provider.
• Notes and calendar: Available, but less mature than chat, tasks and knowledge.

The part I’m working on now is custom apps.

Deft has a module system for custom records and views. I’m also developing an experimental App Author Kit for building and sideloading broader apps into the workspace.

Building a small internal tool is getting easier. Keeping it from becoming another disconnected tab is the part I care about. If you need a custom CRM or workflow tool, I want you to be able to bring it into the place where your team already works.

The CRM module is the first example. I’m building an email client next to test the architecture against something more demanding than records and views. The broader app system is still experimental, with plenty left to build.

Deft is alpha and free to self-host using Docker Compose. You supply the hosting, and any optional paid AI services are separate.

Walkthrough: https://youtu.be/7z9EH4c9k2o
Setup guide: https://deft.ing/docs/quick-start/

A few teams are trying it, but I need more feedback from actual use. If you want to give it a shot and need help setting up, email [maneek@deft.ing](mailto:maneek@deft.ing). If you try it yourself, please share what breaks, feels confusing or simply annoys you. GitHub issues are welcome.

P.S. The walkthrough uses an AI voiceover. I have a stutter and spent a week trying to record it myself, but couldn’t get through it.

Did you ever wonder how good is AI at building Lego models? I built a simple benchmark. GPT 6 Astra is ahead of Opus this time.

Blog post here: https://unifiedsense.com/blog/legobench

Benchmark here: https://legobench.net

I’m doing a 16H run using 16 agents all together in a workflow I’ve only got 78% usage left even after the reset like damn. I’ve given my master agent handling all the other agents to work in unison the ability to adjust agents reasoning level so 6.1 sol, low - medium - high, you get the deal how much do you think it will get done I’m on the pro 5x plan or for you Americans I think it’s the 100$ pro plan.

i'm queing up a chat, and it just crashes constantly. i tried on 3 different accounts, on 6 different computers, on 8 different wifi networks, with and without vpns. normally i like to say it's a skill issue, but i litterally cannot get a single chat going without codex crashing entirely. i'm so fucking dedicated i drove to a mcdonalds to on their wifi to create a brand new chatgpt account on a brand new laptop and codex crashed on chats there too. so idk man. at least i got to have mcdonalds i guess.

Hi everyone,

The ChatGPT extension listed as published by OpenAI in the Microsoft Edge Add-ons Store has stopped working in my sidebar. It displays “chatgpt.com refused to connect.”

ChatGPT still works normally in a regular Edge tab, where I’m logged into the same account.

I’ve already tried:

• Disabling and re-enabling the extension
• Uninstalling and reinstalling it
• Updating Edge and restarting the browser
• Opening ChatGPT in a normal tab before opening the sidebar
• Checking extension permissions — website access is set to all sites
• Checking edge://policy — no apparent policy blocking ChatGPT or extensions

I’m using Windows. Edge says it’s managed by my organization, but the only policy shown is LocalNetworkAccessAllowedForUrls for Microsoft/SharePoint addresses.

Has anyone encountered this? Is there a known fix or a way to diagnose why the sidebar connection is being refused?

Thanks for any suggestions!

I ran an interesting little test in Codex today, and the result was pretty strange.
I had a specific macOS issue: my Synology NAS (DiskStation) appeared in Finder, but clicking “Connect As…” did absolutely nothing. Meanwhile, connecting manually via SMB worked perfectly fine.
So I thought I’d see how two models would handle the exact same problem: GPT-6.1 Sol and GPT-5.6 Sol, both running at Medium reasoning effort.
The result: Both models correctly identified the root cause, but GPT-5.6 got there much more efficiently.
GPT-6.1 Sol went through several rounds of troubleshooting, checking different possible causes and gradually narrowing things down. Eventually, it discovered in the macOS system logs that Finder was trying to connect using AFP, while the manual SMB connection worked without any issues.
GPT-5.6 Sol approached the same problem much more directly. It checked the advertised SMB and AFP services on the network, then used the system logs to identify the exact same issue.
What stood out to me wasn’t just the speed. GPT-5.6 seemed to have a better overall understanding of the problem and reached the solution with fewer unnecessary steps.
I even exported both conversations so I could compare the troubleshooting process afterward.
And here’s what I find confusing.
GPT-6.1 Sol is supposed to be a newer-generation model. Yet, in a relatively straightforward but real-world troubleshooting task, GPT-5.6 Sol actually performed better. Not because 6.1 got the answer wrong, but because it needed more steps and more rounds of investigation to reach the same conclusion.
Of course, you can’t draw broad conclusions from a single test, and I’m not claiming that 5.6 is generally better.
But it’s still strange that a newer model doesn’t necessarily show a clear improvement and, for certain tasks, can actually feel like a step backward.
Has anyone else noticed this in Codex? Do you also find that GPT-5.6 Sol sometimes solves problems faster and with less unnecessary back-and-forth than GPT-6.1 Sol?